EP1989663A4 - Method and apparatus for selective disqualification of digital images - Google Patents
Method and apparatus for selective disqualification of digital imagesInfo
- Publication number
- EP1989663A4 EP1989663A4 EP06789329A EP06789329A EP1989663A4 EP 1989663 A4 EP1989663 A4 EP 1989663A4 EP 06789329 A EP06789329 A EP 06789329A EP 06789329 A EP06789329 A EP 06789329A EP 1989663 A4 EP1989663 A4 EP 1989663A4
- Authority
- EP
- European Patent Office
- Prior art keywords
- image
- eye
- blinking
- scene
- storage devices
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/76—Television signal recording
- H04N5/765—Interface circuits between an apparatus for recording and another apparatus
- H04N5/77—Interface circuits between an apparatus for recording and another apparatus between a recording apparatus and a television camera
- H04N5/772—Interface circuits between an apparatus for recording and another apparatus between a recording apparatus and a television camera the recording apparatus and the television camera being placed in the same enclosure
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/98—Detection or correction of errors, e.g. by rescanning the pattern or by human intervention; Evaluation of the quality of the acquired patterns
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/59—Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
- G06V20/597—Recognising the driver's state or behaviour, e.g. attention or drowsiness
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/193—Preprocessing; Feature extraction
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/61—Control of cameras or camera modules based on recognised objects
- H04N23/611—Control of cameras or camera modules based on recognised objects where the recognised objects include parts of the human body
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N2101/00—Still video cameras
Definitions
- the invention relates to digital image acquisition, and particularly to disqualifying a scene as a candidate for a processed, permanent image due to the presence of one or more unsatisfactory features in the image.
- a method for disqualifying an unsatisfactory scene as an image acquisition control for a camera An analysis of the content of the captured image determines whether the image should be acquired or discarded.
- One example includes human faces. It may be determined whether an image is unsatisfactory based on whether the eyes are closed, partially closed or closing down or moving up during a blinking process. Alternatively, other non-desirable or unsatisfactory expressions or actions such as frowning, covering one's face with a hand or other occluding or shadowing of a facial feature or other key feature of a scene, or rotating the head away from the camera, etc., may be detected.
- a present image of a scene is captured including a face region.
- One or more groups of pixels is/are identified corresponding to the region of interest, such as an an eye region , or a mouth within the face region.
- blink detection it is determined whether the eye region is in a blinking process. If so, then the scene is disqualified as a candidate for a processed, permanent image while the eye is completing the blinking.
- the present image may include a preview image, and the disqualifying may include delaying full resolution capture of an image of the scene.
- the delaying may include ending the disqualifying after a predetermined wait time.
- a preview image may be used. This can provide an indication of a region of interest (ROI) where the eyes may be in the captured image. This provides a fast search in the final image of the mouth or eyes based on spatial information provided from the analysis of preview images.
- ROI region of interest
- the delaying may include predicting when the blinking will be completed and ending the disqualifying at approximately the predicted blink completion time.
- the predicting may include determining a point of a complete blinking process the scene is at, and calculating a remainder time for completion of the blinking.
- the calculating may include multiplying a fraction of the complete blinking process remaining times a predetermined complete blinking process duration.
- the predetermined complete blinking process duration may be programmed based on an average blinking process duration and/or may be determined based on estimating a time from a beginning of the blinking to the present and in view of the fraction representing the point of the complete blinking process the scene is at.
- the estimating may be based on analyzing a temporal capture parameter of one or more previous preview images relative to that of the present preview image.
- the fraction may be determined based on whether the eye that is blinking is opening or closing in the present preview image, and a degree to which the eye is open or shut.
- the method may include determining whether the eye is blinking including determining a degree to which the eye is open or shut.
- the degree to which the eye is open or shut may be determined based on relatively analyzing the present preview image and one or more other preview images relatively acquired within less than a duration of a complete blinking process.
- the determining whether the eye is blinking may include determining a degree of blurriness of one or both eye lids. It may be determined what portion of a pupil, an iris, one or both eye lids or an eye white that is/are showing, or combinations thereof.
- a color analysis of the eye may be performed and differentiating pixels corresponding to an eye lid tone from pixels corresponding to an iris tone or pupil tone or eye white tone, or combinations thereof.
- a shape analysis of the eye may be performed and pixels differentiated as corresponding to an eye lid shape contrast with those corresponding to an iris shape or pupil shape or eye white shape, or combinations thereof.
- the present image may include a full resolution capture image.
- the disqualifying may include foregoing further processing of the present image. It may be determined whether the eye is blinking including determining a degree to which the eye is open or shut. This may include relatively analyzing the present preview image and one or more other preview images relatively acquired within less than a duration of a complete blinking process. The determination of whether the eye is blinking may be based on determining a degree of blurriness of one or both eye lids.
- the method may include determining a portion of a pupil, an iris, one or both eye lids or an eye white that is/are showing, or combinations thereof.
- a color analysis of the eye may be performed and pixels differentiated as corresponding to an eye lid tone contrasted with pixels corresponding to an iris tone or pupil tone or eye white tone, or combinations thereof.
- a shape analysis of the eye may be performed and pixels differentiated as corresponding to an eye lid shape contrasted with pixels corresponding to an iris shape or pupil shape or eye white shape, or combinations thereof.
- the present image may include a full resolution capture image.
- the method may include assembling a combination image including pixels from the present image and open-eye pixels corresponding to the eye that is blinking from a different image.
- the different image may include a preview image or a post- view image or another full resolution image.
- the different image may include a lower resolution than the present image, and the assembling may include upsampling the different image or downsampling the present image, or a combination thereof.
- the method may also include aligning the present image and the different image, including matching an open-eye pixel region to a blinking eye region in the present image.
- the invention may also be implemented to disqualify images out of a selection of images that are part of a stream, such as a video stream.
- An eye region may be identified based on identifying a face region, and analyzing the face region to determine the mouth or eye region therein.
- a new image may be captured due to the disqualifying to replace the present image.
- a pair of images may be captured and analyzed to determine that at least one of the pair of images includes no blinking.
- the interval between multiple captures can be calculated to be longer than a single blink time.
- a warning signal may be provided regarding the blinking so that the photographer may be aware that she may need to take another picture
- the invention in its various alternatives, may address single or multiple faces in a single image, such as a group shot.
- a second eye region of another face may be identified within the scene. Additional eye regions may also be identified within the scene. It may be determined whether the second eye region is in a blinking process. If so, then the method may include disqualifying the scene as a candidate for a processed, permanent image while the second eye is completing the blinking. Capturing or further processing may be disqualified for full resolution images until the eye regions of each face region within the scene include no blinking eyes.
- a further method for automatically disqualifying an unsatisfactory scene as an image acquisition control of a camera.
- the method includes acquiring multiple preview images. Information is extracted from the multiple preview images. One or more changes is/are analyzed in the scene between individual images of the multiple temporary images. Based on the analyzing, it is determined whether one or more unsatisfactory features exist within the scene. The scene is disqualified as a candidate for a processed, permanent image while the one or more unsatisfactory features continue to exist.
- the analyzing may include identifying one or more groups of pixels that correspond to a facial feature having an unsatisfactory configuration.
- the one or more groups of pixels may include an eye group, and the unsatisfactory configuration may include a blinking configuration.
- the one or more groups of pixels may include a mouth configuration, and the unsatisfactory configuration may include a frowning configuration.
- a disqualifying interval may be determined during which no processed, permanent image is to be acquired.
- the analyzing may include identifying one or more groups of pixels that correspond to a facial feature having an unsatisfactory configuration.
- the one or more groups of pixels may include any occlusions such as a hand covering the face or a face that is turned away form the camera.
- processor readable storage devices having processor readable code embodied thereon are also provided.
- the processor readable code is for programming one or more processors to perform a method of disqualifying an unsatisfactory scene as an image acquisition control for a camera, as set forth herein above or below.
- the processor may be embedded as part of the camera or external to the acquisition device.
- the acquisition device may be a hand held camera, a stationary camera, a video camera, a mobile phone equipped with a acquisition device, a hand held device equipped with a acquisition device, a kiosk booth, such as ones used for portraits, a dedicated portrait camera such as one used for security or identifications or generically, any image capture device.
- Figure 1 illustrates a method for disqualifying a scene that includes a blinking eye in accordance with a preferred embodiment.
- Figure 2 illustrates a method of predicting a blinking completion time interval in accordance with a preferred embodiment.
- Figure 3 illustrates a method of determining a degree to which an eye is open or shut in accordance with a preferred embodiment.
- Figure 4a illustrates a method of determining whether to forego further processing of an image in accordance with a preferred embodiment.
- Figure 4b illustrates a method of assembling a combination image in accordance with a preferred embodiment.
- Figure 5 illustrates a preferred embodiment of a workflow of correcting images based on finding eyes in the images.
- Figure 6a illustrates a generic workflow of utilizing eye information in an image to delay image acquisition in accordance with a preferred embodiment.
- Figure 6b illustrates a generic workflow of utilizing face information in a single or a plurality of images to adjust the image rendering parameters prior to outputting the image in accordance with a preferred embodiment.
- Figures 7a-7d illustrate face, eye or mouth detection, or combinations thereof, in accordance with one or more preferred embodiments.
- Figure 8a illustrates a blink detection and correction method in accordance with one or more preferred embodiments.
- Figure 8b describes an illustrative system in accordance with a preferred embodiment to determine whether an eye is blinking in the camera as part of the acquisition process, and whether to capture, discard or store the image, or whether to substitute an open eye for a blinking eye region.
- Figure 9 illustrate an automatic focusing capability in the camera as part of the acquisition process based on the detection of an eye in accordance with one or more preferred embodiments.
- a digital camera is able to decide when a subject's facial expression may be inappropriate, unsatisfactory or non-desirable.
- One example is blinking, and others include frowning occlusions and shadowing.
- the capture device can either not take the picture, delay the acquisition for an appropriate duration, immediately take another picture, warn a camera user, or take steps to enhance the unsatisfactory image later, or combinations of these or other steps.
- the camera may delay taking another picture for a certain amount of time such as roughly 300 milliseconds seconds or for an average blinking interval, or until the blinking is determined to be over.
- the user could be warned before snapping a picture or after the picture has been taken that the subject's eyes may have been closed or semi closed.
- a predictive system that disqualifies images if eyes are closed or partially closed.
- the system predicts when a picture cannot be taken, i.e., those times when a detected blinking process will be ongoing until it is completed.
- Disqualified images may be already captured and disqualified only in a post-capture filtering operation, either within the camera or on an external apparatus.
- the system may take multiple images to enhance the probability that one or more of the images will not be disqualified for including one or more blinking eyes. Such system is useful in the case of a group shot where the probability of one subject in the process of blinking increases as the number of subjects increase.
- the system based on the number of faces in the image, can automatically determine the amount of images to be sequentially taken to provide a probability that at least one of the images will have no blinking eyes that is above a threshold amount, e.g., 50%, 60%, 67%, 70%, 75%, 80%, 90% or 95%.
- a threshold amount e.g. 50%, 60%, 67%, 70%, 75%, 80%, 90% or 95%.
- An image may be generated as a combination of a present image, and a preview, post- view or other full resolution image.
- the combination image may include a face region and some background imagery, wherein one or both eye regions, which are unsatisfactorily closed or partially closed in the present image, are replaced with one or both open eyes from the preview, post- view or other full resolution image.
- This feature may be combined with features presented in United States patent application serial no. 10/608,776, which is assigned to the same assignee as the present application and is hereby incorporated by reference.
- a method of digital image processing using face detection is described. A group of pixels is identified that corresponds to a face within a digital image.
- a second group of pixels is identified that corresponds to another feature within the digital image.
- a re-compositioned image is determined including a new group of pixels for at least one of the face and the other feature.
- the embodiments herein generally refer to a single face within a digital image or scene (e.g., prior to image capture or that may have already been digitally captured), and generally to "an eye". However, these descriptions can extended to both eyes on a single face, and to more than a single face (group shot), and the camera can disqualify the scene if a certain number of one or two, three, four or more eyes are determined to be blinking. The camera is able to perform the disqualifying and/or other operations, as described herein or otherwise, until a high percentage or all of the subjects have one or both of their eyes open.
- the camera will take the picture right after the subject completes a blinking process.
- the present system can be used to disqualify an image having a subject whose eyes are closed, and can take multiple images to prevent having no images that lack blinking.
- One of the images will likely have eyes open for each subject person, and the pictures can have a mixture of pixels combined into a single image with no eyes blinking.
- the camera may decide on the number of images to take based on the number of subjects in the image. The more people, the higher the likelihood of one person blinking, thus more images should be acquired.
- a certain percentage of persons may be blinking in a large group shot, e.g., that is below a certain amount, e.g., 5%, then the number of images can be reduced.
- These threshold numbers and percentage tolerances can be selected by a camera product manufacturer, program developer, or user of a digital image acquisition apparatus. This information may be generated based on analysis of preview images. The preview image may also assist in determining the location of the eyes, so that the post processing analysis can be faster honing into the region of interest as determined by the preview analysis.
- the present system sets a condition under which a picture will not be taken or will not be used or further processed after it has already been taken, and/or where an additional image or images will be taken to replace the unsatisfactory image.
- another advantageous feature of a system in accordance with a preferred embodiment is that it can correct an acquired blink region with a user's eye information from a preview or post- view image or another foil resolution image.
- the present system preferably uses preview images, which generally have lower resolution and may be processed more quickly.
- the present system can also look for comparison of changes in facial features (e.g., of the eyes or mouth), between images as potentially triggering a disqualifying of a scene for an image capture.
- the system may distinguish between a squint which is somewhat permanent or of longer duration during the session than a blink which is more a temporary state.
- the system may also through a comparison of multiple images determine the difference between eyes that are naturally narrow due to the location of the upper-eye-lid or the epicanthal fold, or based on a determined nationality of a subject person, e.g., distinguishing Asian from Caucasian eyes.
- the description herein generally refers to handling a scene wherein an object person is blinking his or her eyes.
- the invention may be applied to other features, e.g., when a person is frowning, or when a person is unsatisfactorily gesturing, talking, eating, having bad hair, or otherwise disposed, or when another person is putting bunny ears on someone, or an animal or other person unexpectedly crosses between the camera and human subject, or the light changes unexpectedly, or the wind blows, or otherwise.
- One or more or all of these disqualifying circumstances may be manually set and/or overridden.
- Figure 1 illustrates a method for disqualifying a scene that includes a blinking eye in accordance with a preferred embodiment.
- a present image of a scene including a face region is acquired at 110.
- the face region is identified at 120, and the face region analyzed to determine one or both eye regions therein.
- One or more groups of pixels corresponding to an eye region within the face region are identified at 130. It is determined whether the eye region is in a blinking process at 140. If the eye is determined to be in a blinking process at 140, then the scene is disqualified as a candidate for a processed, permanent image at 150. At this point, the process can simply stop or start again from the beginning, or a new image may be captured due to the disqualifying in order to replace the present image at 160.
- a warning signal may be provided regarding the blinking at 170.
- Full resolution capture of an image of the scene may be delayed ai 180.
- further processing of a present image may be stopped or a combination image may be assembled as a way of enhancing the disqualified image.
- Figure 2 illustrates a method of predicting a blinking completion time interval in accordance with a preferred embodiment. It is predicted when the blinking process will be completed at 210. and the disqualifying interval will end at the predicted blinking completion time.
- the interval may be set at a predetermined wait time 220. This may be set from a knowledge of an average blink of one quarter of a second or 250 milliseconds, or in a range from approximately 200-400 milli -seconds, or to 0.6, 0.8 or 1.0 seconds, however setting the wait time too long to ensure the blinking is complete disadvantageously permits a second blink to begin or simply makes everyone involved in taking the picture have to wait to too long for the disqualifying period to end. A more precise determination of the end of the blinking process is desired.
- a point of a complete blinking process where a scene is at may be determined at 230 of Figure 2, and then a remainder time can be calculated for completion of the blinking. For example, it may be determined that the blinking process observed is half way complete. In this example, the determined fraction is half or 0.5. This fraction can be advantageously multiplied times a predetermined complete blinking process duration at 240, e.g., 0.25 seconds, to get a completion time remaining of 0.125. " With this more precise determination, there need not be excessive w r ait time for the disqualifying period to end, while still ensuring that the blinking is over before snapping the picture.
- a more precise determination of which images will be disqualified can be determined based on known image capture times.
- a complete blinking process duration based on an average blinking process duration is programmed into the camera or other pre-capture or post-capture processing apparatus.
- a complete blinking process duration is determined based on estimating a time from a beginning of the blinking to present, and in view of the determined fraction. For example, if the determined fraction is one third, and the time from the beginning of the blinking to present is determined to be 0.09 seconds, the complete blink time estimated to be 0.27 seconds, of which 0.18 second remain.
- the estimation may be based on analyzing a temporal capture parameter of one of more previous preview images relative to that of the present image.
- the blinking process may be predicted to end after another 0.16 seconds.
- the fraction is determined, including determining whether the blinking eye is opening or closing, and further determining a degree to which the eye is open or shut.
- the determining a degree to which an eye may be open or shut is further provided at 310 of Figure 3.
- the present image is preferably analyzed at 320 relative to one or more other preview images acquired within less than a duration of a complete blinking process.
- An optional determination of a degree of blurriness at 330 of one or both eye lids may facilitate a determination of blink speed.
- a portion of a pupil, iris, one or both eye lids or an eye white that is/are showing may be determined at 340 to facilitate determining how open or shut the blinking eye is.
- Color analysis 350 and shape analysis 360 may also be performed to differentiate pixels corresponding to features of open eyes such as a pupil, an iris and/or an eye white, from pixels corresponding to features of shut eyes, or eye lids that would appear in an eye region of a present scene.
- Figure 4a illustrates a method of determining whether to forego further processing of an image 410 in accordance with a preferred embodiment.
- determining a degree to which the eye is open or shut 420 is performed for a different purpose than to compute a blinking process completion time.
- a threshold degree of closure of an eye may be preset, e.g., such that when an image is analyzed according to 420, 430, 440, 450, 460, or 470, or combinations thereof, similar to any or a combination of 310-360 of Figure 3, then if the eye is shut to at least the threshold degree or greater, then the scene is disqualified, because the eye is too far shut.
- This can correspond to a situation wherein an eye is not blinking, or where an eye is at the very start or very end of a blinking process, such that the degree to which the eye is open is sufficient for keeping the image.
- Figure 4b illustrates a method of assembling a combination image in accordance with a preferred embodiment.
- a combination image is assembled including pixels from a present image and open eye pixels from a different image that correspond to the eye that is blinking in the present image.
- the different image may be a preview or postview image 490.
- the preview image may be upsampled or the postview image may be downsampled, or a combination thereof.
- the present image and the different image are preferably aligned at 510 to match the open eye pixel region in the preview of postview image to the blinking eye region in the present image.
- Figure 5 illustrates further embodiments. If one or more eyes are determined to be blinking in an image, then that image is preferably disqualified from being further processed in accordance with the following. Alternatively, the blinking determination 140 may be performed somewhere along the way, such as illustrated as an example in Figure 5.
- An image may be opened by the application in block 1102. The software then determines whether eyes or faces, or both, are in the picture as described in block 1106. If no eyes or faces are detected, the software ceases to operate on the image and exits 1110.
- the software may also offer a manual mode, where the user, in block 1116 may inform the software of the existence of eyes, and manually marks them in block 1118.
- the manual selection may be activated automatically if no eyes are found, 1116, or it may even be optionally activated after the automatic stage to let the user, via some user interface to either add more eyes to the automatic selection 1112 or even 1114, remove regions that are mistakenly 1110 identified by the automatic process 1118 as eyes.
- the user may manually select an option that invokes the process as defined in 1106. This option is useful for cases where the user may manually decide that the image can be enhanced or corrected based on the detection of the eyes.
- eyes may be marked, whether automatically of manually, whether in the camera or by the applications, and whether the command to seek the eyes in the image is done manually or automatically, are all included in preferred embodiments herein.
- faces are first detected, and then eyes are detected within the faces.
- the eye detection software may be activated inside the camera as part of the acquisition process, as described in Block 1104.
- the eye detection portion 1106 may be implemented differently to support real time or near real time operation. Such implementation may include sub-sampling of the image, and weighted sampling to reduce the number of pixels on which the computations are performed. This embodiment is further described with reference to Figure 6a.
- the eye detection can then also make use of information provided from preview images to determine the location of the eyes in preview, thus expediting the analysis being performed in a smaller region on the final image.
- the eye detection software may be activated inside the rendering device as part of the output process, as described in Block 1103.
- the eye detection portion 1106 may be implemented either within the rendering device, using the captured image or using a single or plurality of preview images, or within an external driver to such device. This embodiment is further described with reference to Figure 6b.
- the software is ready to operate on the image based on the information generated by the eye-detection, face detection, or other feature-detection stage.
- the tools can be implemented as part of the acquisition, as part of the post-processing, or both.
- blink determination may be performed at this point at 140 (see Figures l-4b and above).
- the image may be disqualified at 1119 if blinking is found, such that further processing, as known to one familiar in the art of digital photography is efficiently foregone.
- a camera is activated at 1000, for example by means of half pressing the shutter, turning on the camera, etc.
- the camera then goes through the normal pre- acquisition stage to determine at 1004 the correct acquisition parameters such as aperture, shutter speed, flash power, gain, color balance, white point, or focus.
- a default set of image attributes particularly related to potential faces in the image, are loaded at 1002.
- Such attributes can be the overall color balance, exposure, contrast, orientation etc.
- a collection of preview images may be analyzed to determine the potential existence of faces in the picture at 1006.
- a region wherein potentially the eyes will be when the full resolution is captured may also be predicted at 1008.
- This alternative technique may include moving on to block 1010 and/or 1002.
- An image is digitally captured onto the sensor at 1010. Such action may be continuously updated, and may or may not include saving such captured image into permanent storage.
- An image-detection process preferably a face detection process, as known to one familiar in the art of image classification and face detection in particular, is applied to the captured image to seek eyes or faces or other features in the image at 1020.
- face detection techniques include, but are not limited to: knowledge-based; feature-invariant; template-matching; appearance-based; color or motion cues; adaboost-based face detector, Viola- Jones, etc.
- the process terminates at 1032.
- the user can manually select, 1034 detected eyes or faces, using some interactive user interface mechanism, by utilizing, for example, a camera display.
- the process can be implemented without a visual user interface by changing the sensitivity or threshold of the detection process.
- this data may be available form a pre-capture process 1003.
- Detecting defined in 1040 may be more than a binary process of selecting whether an eye or a face is detected or not, it may also be designed as part of a process where each of the eyes or faces is given a weight based on size of the eyes or faces, location within the frame, other parameters described herein, which define the importance of the eye or face in relation to other eyes or faces detected.
- the user can manually deselect regions 1044 that were wrongly false detected as eyes or faces. Such selection can be due to the fact that an eye or a face was false detected or when the photographer may wish to concentrate on one of the eyes or faces as the main subject matter and not on other eyes or faces.
- 1046 the user may re-select, or emphasize one or more eyes or faces to indicate that these eyes or faces have a higher importance in the calculation relative to other eyes or faces.
- This process as defined in 1046 further defines the preferred identification process to be a continuous value one as opposed to a binary one. The process can be done utilizing a visual user interface or by adjusting the sensitivity of the detection process.
- the acquisition parameters may change to allow a longer exposure, or open the aperture.
- the image attributes are not necessarily only related to the face regions but can also be in relations to the overall exposure. As an exemplification, if the overall exposure is correct but the faces are underexposed, the camera may shift into a fill-flash mode.
- capture is delayed until detected image attributes match default image attributes.
- An example in accordance with a preferred embodiment is to delay capture until eyes that are blinking and causing the delay are no longer blinking.
- manual override instructions may be entered to take the picture anyway, or to keep a picture or to continue processing of a picture, even though blinking is detected within the picture.
- the picture is taken at 1090, or in accordance with another embodiment, the picture is stored in full resolution.
- a rendering device such as a printer or a display, hereinafter referred to as "the device” is activated at 2100.
- the device is activated at 2100.
- Such activation can be performed for example within a printer, or alternatively within a device connected to the printer such as a PC or a camera.
- the device then goes through a normal pre-rendering stage to determine at 2104, the correct rendering parameters such as tone reproduction, color transformation profiles, gain, color balance, white point and resolution.
- a default set of image attributes particularly related to potential eyes or faces in the image, are loaded at 2102.
- Such attributes can be the overall color balance, exposure, contrast, or orientation, or combinations thereof.
- An image is then digitally downloaded onto the device 2110.
- An image-detection process preferably an eye or a face detection process, is applied to the downloaded image to seek eyes or faces in the image at 2120. If no images are found, the process terminates at 2132 and the device resumes its normal rendering process.
- the user can manually select 2134 detected eyes or faces or other features, using some interactive user interface mechanism, by utilizing, for example, a display on the device.
- the process can be implemented without a visual user interface by changing the sensitivity or threshold of the detection process.
- Detecting in 2130 may be more than a binary process of selecting whether an eye or a face is detected or not. It may also be designed as part of a process where each of the eyes or faces is given a weight based on size of the faces, location within the frame, other parameters described herein, etc., which define the importance of the eye or face in relation to other eyes or faces detected. Alternatively, or in addition, the user can manually deselect regions at 2144 that were wrongly false detected as eyes or faces. Such selection can be due to the fact that an eye or face was false detected or when the photographer may wish to concentrate on one or two of the eyes or one of the faces as the main subject matter and not on other eyes or faces.
- the user may re-select, or emphasize one or more eyes or faces to indicate that these eyes or faces have a higher importance in the calculation relative to other eyes or faces.
- This process as defined in 1146 further defines the preferred identification process to be a continuous value one as opposed to a binary one. The process can be done utilizing a visual user interface or by adjusting the sensitivity of the detection process.
- the eyes or faces or other scene or image features are correctly isolated at 2140, their attributes are compared at 2150 to default values that were predefined in 2102. At least one preferred attribute that the process is looking for is blinking eyes. Such comparison will determine a potential transformation between the two images, in order to reach the same values.
- the image may be disqualified at 2160 if one or more eyes are determined to be blinking.
- the disqualifying may be overridden manually at 2170 or open eye pixels may be substituted from a different image.
- the transformation may be translated to the device rendering parameters, and the image at 2190 may be rendered.
- the process may include a plurality of images. In this case at 2180, the process repeats itself for each image prior to performing the rendering process.
- a practical example is the creation of a thumbnail or contact sheet which is a collection of low resolution images, on a single display instance.
- the rendering parameters may change the tone reproduction curve to lighten the eyes or face.
- the image attributes are not necessarily only related to the eye or face regions, but can also be in relation to an overall tone reproduction.
- Figures 7a-7d which describe automatic rotation of an image based on the location and orientation of eyes, faces, other face features, or other non-facial features, as highlighted in Figure 5 at Block 1130.
- An image of two faces is provided in Figure 7a. Note that the faces may not be identically oriented, and that the faces may be occluding. In this case, both eyes are showing on each face, but only one eye might be showing.
- the software in the eye or face detection stage including the functionality of Figure 5, blocks 1108 and 1118, will mark the two faces or the four eyes of the mother and son, e.g., the faces may be marked as estimations of ellipses 2100 and 2200, respectively.
- the software will determine the main axes of the two faces 2120 and 2220, respectively as well as the secondary axis 2140 and 2240.
- the software may assume that the image is oriented 90 degrees, in the case that the camera is in landscape mode, which is horizontal, or in portrait mode which is vertical or +90 degrees, aka clockwise, or -90 degrees aka counter clockwise.
- the application may also be utilized for any arbitrary rotation value. However, this information may not suffice to decide whether the image is rotated clockwise or counter-clockwise.
- Figure 7c describes the step of extracting the pertinent features of a face, which are usually highly detectable.
- Such objects may include the eyes, 2140, 2160 and 2240, 2260, and the lips, 2180 and 2280, or the nose, eye brows, eye lids, features of the eyes, hair, forehead, chin, ears, etc.
- the combination of the two eyes and the center of the lips creates a triangle 2300 which can be detected not only to determine the orientation of the face but also the rotation of the face relative to a facial shot.
- there are other highly detectable portions of the image which can be labeled and used for orientation detection such as the nostrils, the eyebrows, the hair line, nose bridge and the neck as the physical extension of the face, etc.
- the eyes and lips are provided as an example of such facial features Based on the location of the eyes, if found, and the mouth, the image might ought to be rotated in a counter clockwise direction.
- the color of the eyes may be compared to ensure that the pair of eyes originated from the same person.
- the features of the face may be compared with preview images. Such usage may prevent a case where a double upper eyelid may be mistaken to a semi closed eye.
- FIG. 7c and 7d if the software combined the mouth of 2180 with the eyes of 2260, 2240, the orientation would have been determined as clockwise. In this case, the software detects the correct orientation by comparing the relative size of the mouth and the eyes.
- orientation may be determined based on the geometry of the facial components themselves.
- the eyes are elongated horizontally, which means that when fitting an ellipse on the eye, such as described in blocs 2140 and 2160, it may be desired that the main axis should be horizontal. Similar with the lips which when fitted to an ellipse the main axis should be horizontal.
- the region around the face may also be considered.
- the neck and shoulders which are the only contiguous skin tone connected to the head can be an indication of the orientation and detection of the face.
- a process for determining the orientation of images can be implemented in a preferred embodiment as part of a digital display device. Alternatively, this process can be implemented as part of a digital printing device, or within a digital acquisition device.
- a process can also be implemented as part of a display of multiple images on the same page or screen such as in the display of a contact-sheet or a thumbnail view of images.
- the user may approve or reject the proposed orientation of the images individually or by selecting multiple images at once.
- the orientation of images may be determined based on the information as approved by the user regarding previous images.
- a similar method may be utilized in the pre-acquisition stage, to determine if digital simulation or re- compositioning of an image with open eyes may be advantageous or not, e.g., when an eye is determined to be blinking.
- U.S. patent no. 6,151,073 to Steinberg et al. is hereby incorporated by reference.
- the camera searched for the existence of eyes or faces in the image.
- the eye regions are analyzed at 1470. If the eyes are determined to be sufficiently open at 1474, then the image is left as is at 1478.
- a sub-routine for digitally simulating open eyes is provided.
- a mask or masks define selected regions, i.e., in this example, eye regions.
- the exposure may be increased at 1484 or that may be skipped.
- Shape and/or color processing is performed at 1486 to the selected eye regions. For example, where closed eye lids exist in the original image, pupil, iris and eye white shapes and colors are provided between open eye lids to be substituted over the closed eye lids. Tone reproduction is provided at 1488.
- single or multiple results may be provided to a user.
- the user may select a preferred result at 1492, and the correction is applied at 1498.
- the image may be displayed at 1494 to the user with a parameter to be modified such as iris color or pupil shape. The user then adjusts the extent of the modification at 1496, and the image is corrected at 1498.
- Figure 8b provides another workflow wherein picture taking mode is initiated at 1104 as in Figure 5.
- the image is analyzed at 4820. A determination of whether eyes were found in the image is made at 1106. If not, then exit at 1110. If so, then the eyes are marked at 1108.
- the eye regions are analyzed at 4840, and if the eyes are open 4960, then the picture is either taken, stored (e.g., if the picture was previously taken) or taken and stored at 4880. If the eyes are determined to be closed at 4860, e.g., because blinking is taking place, then the image may be discarded or image capture delayed at 4980, or alternatively the picture may be taken at 4900.
- Figure 9 illustrates a technique involving motion of eye lids.
- a focusing mechanism is activated at 1170.
- the camera seeks the eyes at 1750. If eyes are not detected at 1760, then spatial based auto-focusing techniques may be performed at 1762. If eyes are detected, then regions are marked at 1770. The regions are displayed at 1772.
- the user may take the picture now at 1790. However, the user may move to focus tracking mode at 1780. While the eye lids are moving, e.g., during a blinking process 1782, the eye lid movement is tracked at 1784. A delay or scene disqualification is imposed while the eye lids are moving during the blinking process at 1786. When the disqualifying period ends, the user may take the picture, or the camera may be programmed to automatically take the shot at 1790.
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Families Citing this family (134)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7042505B1 (en) | 1997-10-09 | 2006-05-09 | Fotonation Ireland Ltd. | Red-eye filter method and apparatus |
US7630006B2 (en) | 1997-10-09 | 2009-12-08 | Fotonation Ireland Limited | Detecting red eye filter and apparatus using meta-data |
US7738015B2 (en) | 1997-10-09 | 2010-06-15 | Fotonation Vision Limited | Red-eye filter method and apparatus |
US7620218B2 (en) | 2006-08-11 | 2009-11-17 | Fotonation Ireland Limited | Real-time face tracking with reference images |
US7606417B2 (en) | 2004-08-16 | 2009-10-20 | Fotonation Vision Limited | Foreground/background segmentation in digital images with differential exposure calculations |
US8330831B2 (en) | 2003-08-05 | 2012-12-11 | DigitalOptics Corporation Europe Limited | Method of gathering visual meta data using a reference image |
US7440593B1 (en) | 2003-06-26 | 2008-10-21 | Fotonation Vision Limited | Method of improving orientation and color balance of digital images using face detection information |
US8180173B2 (en) * | 2007-09-21 | 2012-05-15 | DigitalOptics Corporation Europe Limited | Flash artifact eye defect correction in blurred images using anisotropic blurring |
US8593542B2 (en) | 2005-12-27 | 2013-11-26 | DigitalOptics Corporation Europe Limited | Foreground/background separation using reference images |
US7574016B2 (en) | 2003-06-26 | 2009-08-11 | Fotonation Vision Limited | Digital image processing using face detection information |
US9129381B2 (en) | 2003-06-26 | 2015-09-08 | Fotonation Limited | Modification of post-viewing parameters for digital images using image region or feature information |
US7471846B2 (en) | 2003-06-26 | 2008-12-30 | Fotonation Vision Limited | Perfecting the effect of flash within an image acquisition devices using face detection |
US8264576B2 (en) * | 2007-03-05 | 2012-09-11 | DigitalOptics Corporation Europe Limited | RGBW sensor array |
US8682097B2 (en) | 2006-02-14 | 2014-03-25 | DigitalOptics Corporation Europe Limited | Digital image enhancement with reference images |
US7920723B2 (en) | 2005-11-18 | 2011-04-05 | Tessera Technologies Ireland Limited | Two stage detection for photographic eye artifacts |
US7844076B2 (en) | 2003-06-26 | 2010-11-30 | Fotonation Vision Limited | Digital image processing using face detection and skin tone information |
US9692964B2 (en) | 2003-06-26 | 2017-06-27 | Fotonation Limited | Modification of post-viewing parameters for digital images using image region or feature information |
US8498452B2 (en) | 2003-06-26 | 2013-07-30 | DigitalOptics Corporation Europe Limited | Digital image processing using face detection information |
US8417055B2 (en) | 2007-03-05 | 2013-04-09 | DigitalOptics Corporation Europe Limited | Image processing method and apparatus |
US7792335B2 (en) | 2006-02-24 | 2010-09-07 | Fotonation Vision Limited | Method and apparatus for selective disqualification of digital images |
US7336821B2 (en) | 2006-02-14 | 2008-02-26 | Fotonation Vision Limited | Automatic detection and correction of non-red eye flash defects |
US8494286B2 (en) * | 2008-02-05 | 2013-07-23 | DigitalOptics Corporation Europe Limited | Face detection in mid-shot digital images |
US8989516B2 (en) | 2007-09-18 | 2015-03-24 | Fotonation Limited | Image processing method and apparatus |
US7636486B2 (en) | 2004-11-10 | 2009-12-22 | Fotonation Ireland Ltd. | Method of determining PSF using multiple instances of a nominally similar scene |
US8896725B2 (en) | 2007-06-21 | 2014-11-25 | Fotonation Limited | Image capture device with contemporaneous reference image capture mechanism |
US9160897B2 (en) | 2007-06-14 | 2015-10-13 | Fotonation Limited | Fast motion estimation method |
US7639889B2 (en) | 2004-11-10 | 2009-12-29 | Fotonation Ireland Ltd. | Method of notifying users regarding motion artifacts based on image analysis |
US8989453B2 (en) | 2003-06-26 | 2015-03-24 | Fotonation Limited | Digital image processing using face detection information |
US7565030B2 (en) | 2003-06-26 | 2009-07-21 | Fotonation Vision Limited | Detecting orientation of digital images using face detection information |
US7792970B2 (en) | 2005-06-17 | 2010-09-07 | Fotonation Vision Limited | Method for establishing a paired connection between media devices |
US8254674B2 (en) | 2004-10-28 | 2012-08-28 | DigitalOptics Corporation Europe Limited | Analyzing partial face regions for red-eye detection in acquired digital images |
US8155397B2 (en) | 2007-09-26 | 2012-04-10 | DigitalOptics Corporation Europe Limited | Face tracking in a camera processor |
US7269292B2 (en) | 2003-06-26 | 2007-09-11 | Fotonation Vision Limited | Digital image adjustable compression and resolution using face detection information |
US7970182B2 (en) | 2005-11-18 | 2011-06-28 | Tessera Technologies Ireland Limited | Two stage detection for photographic eye artifacts |
US7689009B2 (en) | 2005-11-18 | 2010-03-30 | Fotonation Vision Ltd. | Two stage detection for photographic eye artifacts |
US8199222B2 (en) | 2007-03-05 | 2012-06-12 | DigitalOptics Corporation Europe Limited | Low-light video frame enhancement |
US8948468B2 (en) | 2003-06-26 | 2015-02-03 | Fotonation Limited | Modification of viewing parameters for digital images using face detection information |
US8170294B2 (en) | 2006-11-10 | 2012-05-01 | DigitalOptics Corporation Europe Limited | Method of detecting redeye in a digital image |
US8036458B2 (en) | 2007-11-08 | 2011-10-11 | DigitalOptics Corporation Europe Limited | Detecting redeye defects in digital images |
US20050140801A1 (en) * | 2003-08-05 | 2005-06-30 | Yury Prilutsky | Optimized performance and performance for red-eye filter method and apparatus |
US8520093B2 (en) | 2003-08-05 | 2013-08-27 | DigitalOptics Corporation Europe Limited | Face tracker and partial face tracker for red-eye filter method and apparatus |
US9412007B2 (en) | 2003-08-05 | 2016-08-09 | Fotonation Limited | Partial face detector red-eye filter method and apparatus |
US8320641B2 (en) | 2004-10-28 | 2012-11-27 | DigitalOptics Corporation Europe Limited | Method and apparatus for red-eye detection using preview or other reference images |
US7639888B2 (en) | 2004-11-10 | 2009-12-29 | Fotonation Ireland Ltd. | Method and apparatus for initiating subsequent exposures based on determination of motion blurring artifacts |
US7315631B1 (en) | 2006-08-11 | 2008-01-01 | Fotonation Vision Limited | Real-time face tracking in a digital image acquisition device |
US7715597B2 (en) | 2004-12-29 | 2010-05-11 | Fotonation Ireland Limited | Method and component for image recognition |
US20110102553A1 (en) * | 2007-02-28 | 2011-05-05 | Tessera Technologies Ireland Limited | Enhanced real-time face models from stereo imaging |
US8995715B2 (en) | 2010-10-26 | 2015-03-31 | Fotonation Limited | Face or other object detection including template matching |
US8503800B2 (en) | 2007-03-05 | 2013-08-06 | DigitalOptics Corporation Europe Limited | Illumination detection using classifier chains |
EP1748378B1 (en) * | 2005-07-26 | 2009-09-16 | Canon Kabushiki Kaisha | Image capturing apparatus and image capturing method |
US20090060289A1 (en) * | 2005-09-28 | 2009-03-05 | Alex Shah | Digital Image Search System And Method |
US7599577B2 (en) | 2005-11-18 | 2009-10-06 | Fotonation Vision Limited | Method and apparatus of correcting hybrid flash artifacts in digital images |
IES20070229A2 (en) | 2006-06-05 | 2007-10-03 | Fotonation Vision Ltd | Image acquisition method and apparatus |
DE602007012246D1 (en) | 2006-06-12 | 2011-03-10 | Tessera Tech Ireland Ltd | PROGRESS IN EXTENDING THE AAM TECHNIQUES FROM GRAY CALENDAR TO COLOR PICTURES |
US7916897B2 (en) | 2006-08-11 | 2011-03-29 | Tessera Technologies Ireland Limited | Face tracking for controlling imaging parameters |
US7403643B2 (en) | 2006-08-11 | 2008-07-22 | Fotonation Vision Limited | Real-time face tracking in a digital image acquisition device |
JP4137969B2 (en) * | 2006-12-04 | 2008-08-20 | アイシン精機株式会社 | Eye detection device, eye detection method, and program |
US8055067B2 (en) | 2007-01-18 | 2011-11-08 | DigitalOptics Corporation Europe Limited | Color segmentation |
JP4895847B2 (en) * | 2007-02-08 | 2012-03-14 | アイシン精機株式会社 | 瞼 Detection device and program |
DE602008001607D1 (en) | 2007-02-28 | 2010-08-05 | Fotonation Vision Ltd | SEPARATION OF DIRECTIONAL ILLUMINATION VARIABILITY IN STATISTICAL FACE MODELING BASED ON TEXTURE SPACE MODULES |
WO2008107002A1 (en) | 2007-03-05 | 2008-09-12 | Fotonation Vision Limited | Face searching and detection in a digital image acquisition device |
WO2008109708A1 (en) | 2007-03-05 | 2008-09-12 | Fotonation Vision Limited | Red eye false positive filtering using face location and orientation |
US7773118B2 (en) | 2007-03-25 | 2010-08-10 | Fotonation Vision Limited | Handheld article with movement discrimination |
US7916971B2 (en) | 2007-05-24 | 2011-03-29 | Tessera Technologies Ireland Limited | Image processing method and apparatus |
JP4764381B2 (en) * | 2007-06-05 | 2011-08-31 | 株式会社コナミデジタルエンタテインメント | Image processing apparatus, image processing method, and program |
US7844085B2 (en) * | 2007-06-07 | 2010-11-30 | Seiko Epson Corporation | Pairwise feature learning with boosting for use in face detection |
US8031970B2 (en) * | 2007-08-27 | 2011-10-04 | Arcsoft, Inc. | Method of restoring closed-eye portrait photo |
US8503818B2 (en) | 2007-09-25 | 2013-08-06 | DigitalOptics Corporation Europe Limited | Eye defect detection in international standards organization images |
JP5169139B2 (en) | 2007-10-25 | 2013-03-27 | 株式会社ニコン | Camera and image recording program |
US8022982B2 (en) * | 2008-01-02 | 2011-09-20 | Sony Ericsson Mobile Communications Ab | Camera system and method for operating a camera system |
US8212864B2 (en) | 2008-01-30 | 2012-07-03 | DigitalOptics Corporation Europe Limited | Methods and apparatuses for using image acquisition data to detect and correct image defects |
JP5055166B2 (en) * | 2008-02-29 | 2012-10-24 | キヤノン株式会社 | Eye open / closed degree determination device, method and program, and imaging device |
JP5249359B2 (en) * | 2008-03-14 | 2013-07-31 | メタイオ ゲゼルシャフト ミット ベシュレンクテル ハフツング | Method and system for displaying images generated by at least one camera |
KR101448536B1 (en) * | 2008-03-21 | 2014-10-08 | 삼성전자주식회사 | Digital photographing apparatus, method for controlling the same, and recording medium storing program to implement the method |
US7855737B2 (en) | 2008-03-26 | 2010-12-21 | Fotonation Ireland Limited | Method of making a digital camera image of a scene including the camera user |
SG157974A1 (en) * | 2008-06-18 | 2010-01-29 | Creative Tech Ltd | An image capturing apparatus able to be draped on a stand and a method for providing an image with eye-to-eye contact with a recipient |
WO2010012448A2 (en) | 2008-07-30 | 2010-02-04 | Fotonation Ireland Limited | Automatic face and skin beautification using face detection |
US8081254B2 (en) | 2008-08-14 | 2011-12-20 | DigitalOptics Corporation Europe Limited | In-camera based method of detecting defect eye with high accuracy |
US8345922B2 (en) * | 2008-09-03 | 2013-01-01 | Denso Corporation | Apparatus for detecting a pupil, program for the same, and method for detecting a pupil |
JP4748244B2 (en) * | 2009-03-31 | 2011-08-17 | カシオ計算機株式会社 | Image selection apparatus, image selection method, and program |
US20100302394A1 (en) * | 2009-05-28 | 2010-12-02 | Phanish Hanagal Srinivasa Rao | Blinked eye artifact removal for a digital imaging device |
JP5456159B2 (en) | 2009-05-29 | 2014-03-26 | デジタルオプティックス・コーポレイション・ヨーロッパ・リミテッド | Method and apparatus for separating the top of the foreground from the background |
US8379917B2 (en) | 2009-10-02 | 2013-02-19 | DigitalOptics Corporation Europe Limited | Face recognition performance using additional image features |
CN102098493B (en) * | 2009-12-11 | 2014-04-30 | 鸿富锦精密工业(深圳)有限公司 | System and method for adjusting monitor parameters |
US10080006B2 (en) | 2009-12-11 | 2018-09-18 | Fotonation Limited | Stereoscopic (3D) panorama creation on handheld device |
US20110205383A1 (en) * | 2010-02-24 | 2011-08-25 | Research In Motion Limited | Eye blink avoidance during image acquisition in a mobile communications device with digital camera functionality |
EP2360620A1 (en) * | 2010-02-24 | 2011-08-24 | Research In Motion Limited | Eye blink avoidance during image acquisition in a mobile communications device with digital camera functionality |
US8692867B2 (en) | 2010-03-05 | 2014-04-08 | DigitalOptics Corporation Europe Limited | Object detection and rendering for wide field of view (WFOV) image acquisition systems |
CN102193621A (en) * | 2010-03-17 | 2011-09-21 | 三星电子(中国)研发中心 | Vision-based interactive electronic equipment control system and control method thereof |
US8503722B2 (en) * | 2010-04-01 | 2013-08-06 | Broadcom Corporation | Method and system for determining how to handle processing of an image based on motion |
US8369581B2 (en) | 2010-06-24 | 2013-02-05 | Eastman Kodak Company | Automatic appeal measurement method |
US8369582B2 (en) | 2010-06-24 | 2013-02-05 | Eastman Kodak Company | Automatic appeal measurement system |
US8363085B2 (en) | 2010-07-06 | 2013-01-29 | DigitalOptics Corporation Europe Limited | Scene background blurring including determining a depth map |
US8971628B2 (en) | 2010-07-26 | 2015-03-03 | Fotonation Limited | Face detection using division-generated haar-like features for illumination invariance |
US8970770B2 (en) | 2010-09-28 | 2015-03-03 | Fotonation Limited | Continuous autofocus based on face detection and tracking |
KR101728042B1 (en) | 2010-10-01 | 2017-04-18 | 삼성전자주식회사 | Digital photographing apparatus and control method thereof |
US8308379B2 (en) | 2010-12-01 | 2012-11-13 | Digitaloptics Corporation | Three-pole tilt control system for camera module |
US8836777B2 (en) | 2011-02-25 | 2014-09-16 | DigitalOptics Corporation Europe Limited | Automatic detection of vertical gaze using an embedded imaging device |
US8982180B2 (en) | 2011-03-31 | 2015-03-17 | Fotonation Limited | Face and other object detection and tracking in off-center peripheral regions for nonlinear lens geometries |
US8723959B2 (en) | 2011-03-31 | 2014-05-13 | DigitalOptics Corporation Europe Limited | Face and other object tracking in off-center peripheral regions for nonlinear lens geometries |
US8860816B2 (en) | 2011-03-31 | 2014-10-14 | Fotonation Limited | Scene enhancements in off-center peripheral regions for nonlinear lens geometries |
US8896703B2 (en) | 2011-03-31 | 2014-11-25 | Fotonation Limited | Superresolution enhancment of peripheral regions in nonlinear lens geometries |
US9294667B2 (en) | 2012-03-10 | 2016-03-22 | Digitaloptics Corporation | MEMS auto focus miniature camera module with fixed and movable lens groups |
WO2013136053A1 (en) | 2012-03-10 | 2013-09-19 | Digitaloptics Corporation | Miniature camera module with mems-actuated autofocus |
WO2014072837A2 (en) | 2012-06-07 | 2014-05-15 | DigitalOptics Corporation Europe Limited | Mems fast focus camera module |
CN102799878B (en) * | 2012-07-09 | 2015-10-21 | 中国科学技术大学 | Iris face fusion acquisition device |
US10192290B2 (en) * | 2012-07-23 | 2019-01-29 | Sheri Engler | Interface for revealing latent figures within images |
US9001268B2 (en) | 2012-08-10 | 2015-04-07 | Nan Chang O-Film Optoelectronics Technology Ltd | Auto-focus camera module with flexible printed circuit extension |
US9007520B2 (en) | 2012-08-10 | 2015-04-14 | Nanchang O-Film Optoelectronics Technology Ltd | Camera module with EMI shield |
US9242602B2 (en) | 2012-08-27 | 2016-01-26 | Fotonation Limited | Rearview imaging systems for vehicle |
US9055207B2 (en) | 2012-12-31 | 2015-06-09 | Digitaloptics Corporation | Auto-focus camera module with MEMS distance measurement |
US10402846B2 (en) | 2013-05-21 | 2019-09-03 | Fotonation Limited | Anonymizing facial expression data with a smart-cam |
WO2014190509A1 (en) * | 2013-05-29 | 2014-12-04 | Nokia Corporation | An apparatus and associated methods |
WO2015029371A1 (en) * | 2013-08-30 | 2015-03-05 | パナソニックIpマネジメント株式会社 | Makeup assistance device, makeup assistance method, and makeup assistance program |
JP5971216B2 (en) * | 2013-09-20 | 2016-08-17 | カシオ計算機株式会社 | Image processing apparatus, image processing method, and program |
US9549118B2 (en) * | 2014-03-10 | 2017-01-17 | Qualcomm Incorporated | Blink and averted gaze avoidance in photographic images |
CN103927554A (en) * | 2014-05-07 | 2014-07-16 | 中国标准化研究院 | Image sparse representation facial expression feature extraction system and method based on topological structure |
US9769367B2 (en) | 2015-08-07 | 2017-09-19 | Google Inc. | Speech and computer vision-based control |
US10225511B1 (en) | 2015-12-30 | 2019-03-05 | Google Llc | Low power framework for controlling image sensor mode in a mobile image capture device |
US9836484B1 (en) | 2015-12-30 | 2017-12-05 | Google Llc | Systems and methods that leverage deep learning to selectively store images at a mobile image capture device |
US9838641B1 (en) | 2015-12-30 | 2017-12-05 | Google Llc | Low power framework for processing, compressing, and transmitting images at a mobile image capture device |
US10732809B2 (en) | 2015-12-30 | 2020-08-04 | Google Llc | Systems and methods for selective retention and editing of images captured by mobile image capture device |
US9836819B1 (en) | 2015-12-30 | 2017-12-05 | Google Llc | Systems and methods for selective retention and editing of images captured by mobile image capture device |
US10321050B2 (en) | 2016-11-29 | 2019-06-11 | International Business Machines Corporation | Determining optimal photograph capture timing based on data from wearable computer eyewear devices |
JP6866142B2 (en) | 2016-12-09 | 2021-04-28 | キヤノン株式会社 | Programs, image processing equipment, and image processing methods |
CN108319953B (en) * | 2017-07-27 | 2019-07-16 | 腾讯科技(深圳)有限公司 | Occlusion detection method and device, electronic equipment and the storage medium of target object |
JP7072378B2 (en) * | 2017-12-13 | 2022-05-20 | キヤノン株式会社 | Image generator and its control method, image generation system, program |
CN108492266B (en) * | 2018-03-18 | 2020-10-09 | Oppo广东移动通信有限公司 | Image processing method, image processing device, storage medium and electronic equipment |
CN108521547A (en) * | 2018-04-24 | 2018-09-11 | 京东方科技集团股份有限公司 | Image processing method, device and equipment |
CN111557007B (en) * | 2018-07-16 | 2022-08-19 | 荣耀终端有限公司 | Method for detecting opening and closing states of eyes and electronic equipment |
CN109199411B (en) * | 2018-09-28 | 2021-04-09 | 南京工程学院 | Case-conscious person identification method based on model fusion |
JP7277149B2 (en) * | 2019-01-18 | 2023-05-18 | キヤノン株式会社 | Imaging device and its control method |
CN114270306A (en) * | 2019-08-27 | 2022-04-01 | 西门子股份公司 | Application program development and deployment method, device and computer readable medium |
US11568540B2 (en) * | 2019-10-07 | 2023-01-31 | Optos Plc | System, method, and computer-readable medium for rejecting full and partial blinks for retinal tracking |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20030160879A1 (en) * | 2002-02-28 | 2003-08-28 | Robins Mark Nelson | White eye portraiture system and method |
US20030190090A1 (en) * | 2002-04-09 | 2003-10-09 | Beeman Edward S. | System and method for digital-image enhancement |
US20040170397A1 (en) * | 1999-06-03 | 2004-09-02 | Fuji Photo Film Co., Ltd. | Camera and method of photographing good image |
US20040223629A1 (en) * | 2003-05-06 | 2004-11-11 | Viswis, Inc. | Facial surveillance system and method |
EP1748378A1 (en) * | 2005-07-26 | 2007-01-31 | Canon Kabushiki Kaisha | Image capturing apparatus and image capturing method |
Family Cites Families (168)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US583616A (en) * | 1897-06-01 | Perfo rating-machine | ||
US4047187A (en) | 1974-04-01 | 1977-09-06 | Canon Kabushiki Kaisha | System for exposure measurement and/or focus detection by means of image senser |
US4317991A (en) | 1980-03-12 | 1982-03-02 | Honeywell Inc. | Digital auto focus system utilizing a photodetector array |
US4367027A (en) | 1980-03-12 | 1983-01-04 | Honeywell Inc. | Active auto focus system improvement |
US4299464A (en) * | 1980-08-04 | 1981-11-10 | Eastman Kodak Company | Method and apparatus for reducing the incidence of eye closures during photographing of a human subject |
JPS61105978A (en) | 1984-10-30 | 1986-05-24 | Sanyo Electric Co Ltd | Automatic focusing circuit |
US5291234A (en) | 1987-02-04 | 1994-03-01 | Asahi Kogaku Kogyo Kabushiki Kaisha | Auto optical focus detecting device and eye direction detecting optical system |
US5384912A (en) | 1987-10-30 | 1995-01-24 | New Microtime Inc. | Real time video image processing system |
US5018017A (en) | 1987-12-25 | 1991-05-21 | Kabushiki Kaisha Toshiba | Electronic still camera and image recording method thereof |
US5227837A (en) | 1989-05-12 | 1993-07-13 | Fuji Photo Film Co., Ltd. | Photograph printing method |
US5063603A (en) | 1989-11-06 | 1991-11-05 | David Sarnoff Research Center, Inc. | Dynamic method for recognizing objects and image processing system therefor |
US5164831A (en) | 1990-03-15 | 1992-11-17 | Eastman Kodak Company | Electronic still camera providing multi-format storage of full and reduced resolution images |
GB9019538D0 (en) | 1990-09-07 | 1990-10-24 | Philips Electronic Associated | Tracking a moving object |
JP2748678B2 (en) | 1990-10-09 | 1998-05-13 | 松下電器産業株式会社 | Gradation correction method and gradation correction device |
US5164992A (en) | 1990-11-01 | 1992-11-17 | Massachusetts Institute Of Technology | Face recognition system |
JP2790562B2 (en) | 1992-01-06 | 1998-08-27 | 富士写真フイルム株式会社 | Image processing method |
US5638136A (en) | 1992-01-13 | 1997-06-10 | Mitsubishi Denki Kabushiki Kaisha | Method and apparatus for detecting flesh tones in an image |
US5488429A (en) | 1992-01-13 | 1996-01-30 | Mitsubishi Denki Kabushiki Kaisha | Video signal processor for detecting flesh tones in am image |
US5680481A (en) | 1992-05-26 | 1997-10-21 | Ricoh Corporation | Facial feature extraction method and apparatus for a neural network acoustic and visual speech recognition system |
JP3298072B2 (en) | 1992-07-10 | 2002-07-02 | ソニー株式会社 | Video camera system |
US5311240A (en) | 1992-11-03 | 1994-05-10 | Eastman Kodak Company | Technique suited for use in multi-zone autofocusing cameras for improving image quality for non-standard display sizes and/or different focal length photographing modes |
KR100276681B1 (en) | 1992-11-07 | 2001-01-15 | 이데이 노부유끼 | Video camera system |
JPH06178261A (en) | 1992-12-07 | 1994-06-24 | Nikon Corp | Digital still camera |
JP2983407B2 (en) | 1993-03-31 | 1999-11-29 | 三菱電機株式会社 | Image tracking device |
US5432863A (en) | 1993-07-19 | 1995-07-11 | Eastman Kodak Company | Automated detection and correction of eye color defects due to flash illumination |
US5781650A (en) | 1994-02-18 | 1998-07-14 | University Of Central Florida | Automatic feature detection and age classification of human faces in digital images |
US5835616A (en) | 1994-02-18 | 1998-11-10 | University Of Central Florida | Face detection using templates |
US6115509A (en) | 1994-03-10 | 2000-09-05 | International Business Machines Corp | High volume document image archive system and method |
US5774754A (en) | 1994-04-26 | 1998-06-30 | Minolta Co., Ltd. | Camera capable of previewing a photographed image |
US5678098A (en) | 1994-06-09 | 1997-10-14 | Fuji Photo Film Co., Ltd. | Method and apparatus for controlling exposure of camera |
US5692065A (en) | 1994-08-18 | 1997-11-25 | International Business Machines Corporation | Apparatus and method for determining image quality |
US5572596A (en) * | 1994-09-02 | 1996-11-05 | David Sarnoff Research Center, Inc. | Automated, non-invasive iris recognition system and method |
US5802361A (en) | 1994-09-30 | 1998-09-01 | Apple Computer, Inc. | Method and system for searching graphic images and videos |
US5496106A (en) | 1994-12-13 | 1996-03-05 | Apple Computer, Inc. | System and method for generating a contrast overlay as a focus assist for an imaging device |
US5870138A (en) | 1995-03-31 | 1999-02-09 | Hitachi, Ltd. | Facial image processing |
US5724456A (en) | 1995-03-31 | 1998-03-03 | Polaroid Corporation | Brightness adjustment of images using digital scene analysis |
US5710833A (en) | 1995-04-20 | 1998-01-20 | Massachusetts Institute Of Technology | Detection, recognition and coding of complex objects using probabilistic eigenspace analysis |
US5842194A (en) | 1995-07-28 | 1998-11-24 | Mitsubishi Denki Kabushiki Kaisha | Method of recognizing images of faces or general images using fuzzy combination of multiple resolutions |
JP3426060B2 (en) * | 1995-07-28 | 2003-07-14 | 三菱電機株式会社 | Face image processing device |
US5774591A (en) * | 1995-12-15 | 1998-06-30 | Xerox Corporation | Apparatus and method for recognizing facial expressions and facial gestures in a sequence of images |
US5802220A (en) | 1995-12-15 | 1998-09-01 | Xerox Corporation | Apparatus and method for tracking facial motion through a sequence of images |
US5633678A (en) | 1995-12-20 | 1997-05-27 | Eastman Kodak Company | Electronic still camera for capturing and categorizing images |
US6151073A (en) | 1996-03-28 | 2000-11-21 | Fotonation, Inc. | Intelligent camera flash system |
US5802208A (en) | 1996-05-06 | 1998-09-01 | Lucent Technologies Inc. | Face recognition using DCT-based feature vectors |
US6188776B1 (en) | 1996-05-21 | 2001-02-13 | Interval Research Corporation | Principle component analysis of images for the automatic location of control points |
US5991456A (en) | 1996-05-29 | 1999-11-23 | Science And Technology Corporation | Method of improving a digital image |
US5978519A (en) | 1996-08-06 | 1999-11-02 | Xerox Corporation | Automatic image cropping |
US5963656A (en) | 1996-09-30 | 1999-10-05 | International Business Machines Corporation | System and method for determining the quality of fingerprint images |
US5818975A (en) | 1996-10-28 | 1998-10-06 | Eastman Kodak Company | Method and apparatus for area selective exposure adjustment |
US6765612B1 (en) | 1996-12-09 | 2004-07-20 | Flashpoint Technology, Inc. | Method and system for naming images captured by a digital camera |
JP3512992B2 (en) | 1997-01-07 | 2004-03-31 | 株式会社東芝 | Image processing apparatus and image processing method |
JPH10208047A (en) | 1997-01-23 | 1998-08-07 | Nissan Motor Co Ltd | On-vehicle traveling environment recognizing device |
US6249315B1 (en) | 1997-03-24 | 2001-06-19 | Jack M. Holm | Strategy for pictorial digital image processing |
US6215898B1 (en) | 1997-04-15 | 2001-04-10 | Interval Research Corporation | Data processing system and method |
US6125192A (en) | 1997-04-21 | 2000-09-26 | Digital Persona, Inc. | Fingerprint recognition system |
US6803989B2 (en) | 1997-07-15 | 2004-10-12 | Silverbrook Research Pty Ltd | Image printing apparatus including a microcontroller |
AUPO798697A0 (en) | 1997-07-15 | 1997-08-07 | Silverbrook Research Pty Ltd | Data processing method and apparatus (ART51) |
US6188777B1 (en) | 1997-08-01 | 2001-02-13 | Interval Research Corporation | Method and apparatus for personnel detection and tracking |
US6407777B1 (en) | 1997-10-09 | 2002-06-18 | Deluca Michael Joseph | Red-eye filter method and apparatus |
US7738015B2 (en) | 1997-10-09 | 2010-06-15 | Fotonation Vision Limited | Red-eye filter method and apparatus |
US6128397A (en) | 1997-11-21 | 2000-10-03 | Justsystem Pittsburgh Research Center | Method for finding all frontal faces in arbitrarily complex visual scenes |
US6268939B1 (en) | 1998-01-08 | 2001-07-31 | Xerox Corporation | Method and apparatus for correcting luminance and chrominance data in digital color images |
US6148092A (en) | 1998-01-08 | 2000-11-14 | Sharp Laboratories Of America, Inc | System for detecting skin-tone regions within an image |
GB2333590A (en) | 1998-01-23 | 1999-07-28 | Sharp Kk | Detecting a face-like region |
US6400830B1 (en) | 1998-02-06 | 2002-06-04 | Compaq Computer Corporation | Technique for tracking objects through a series of images |
US6556708B1 (en) | 1998-02-06 | 2003-04-29 | Compaq Computer Corporation | Technique for classifying objects within an image |
US6192149B1 (en) | 1998-04-08 | 2001-02-20 | Xerox Corporation | Method and apparatus for automatic detection of image target gamma |
US6301370B1 (en) | 1998-04-13 | 2001-10-09 | Eyematic Interfaces, Inc. | Face recognition from video images |
US6097470A (en) | 1998-05-28 | 2000-08-01 | Eastman Kodak Company | Digital photofinishing system including scene balance, contrast normalization, and image sharpening digital image processing |
AUPP400998A0 (en) | 1998-06-10 | 1998-07-02 | Canon Kabushiki Kaisha | Face detection in digital images |
US6404900B1 (en) | 1998-06-22 | 2002-06-11 | Sharp Laboratories Of America, Inc. | Method for robust human face tracking in presence of multiple persons |
DE19837004C1 (en) | 1998-08-14 | 2000-03-09 | Christian Eckes | Process for recognizing objects in digitized images |
GB2341231A (en) | 1998-09-05 | 2000-03-08 | Sharp Kk | Face detection in an image |
US6456732B1 (en) | 1998-09-11 | 2002-09-24 | Hewlett-Packard Company | Automatic rotation, cropping and scaling of images for printing |
US6606398B2 (en) | 1998-09-30 | 2003-08-12 | Intel Corporation | Automatic cataloging of people in digital photographs |
JP3291259B2 (en) | 1998-11-11 | 2002-06-10 | キヤノン株式会社 | Image processing method and recording medium |
JP2002531901A (en) | 1998-12-02 | 2002-09-24 | ザ・ビクトリア・ユニバーシテイ・オブ・マンチエスター | Determination of face subspace |
US6263113B1 (en) | 1998-12-11 | 2001-07-17 | Philips Electronics North America Corp. | Method for detecting a face in a digital image |
US6473199B1 (en) | 1998-12-18 | 2002-10-29 | Eastman Kodak Company | Correcting exposure and tone scale of digital images captured by an image capture device |
US6396599B1 (en) | 1998-12-21 | 2002-05-28 | Eastman Kodak Company | Method and apparatus for modifying a portion of an image in accordance with colorimetric parameters |
US6282317B1 (en) | 1998-12-31 | 2001-08-28 | Eastman Kodak Company | Method for automatic determination of main subjects in photographic images |
US6438264B1 (en) | 1998-12-31 | 2002-08-20 | Eastman Kodak Company | Method for compensating image color when adjusting the contrast of a digital color image |
US6421468B1 (en) | 1999-01-06 | 2002-07-16 | Seiko Epson Corporation | Method and apparatus for sharpening an image by scaling elements of a frequency-domain representation |
US7038715B1 (en) | 1999-01-19 | 2006-05-02 | Texas Instruments Incorporated | Digital still camera with high-quality portrait mode |
US6393148B1 (en) | 1999-05-13 | 2002-05-21 | Hewlett-Packard Company | Contrast enhancement of an image using luminance and RGB statistical metrics |
EP1139286A1 (en) | 1999-05-18 | 2001-10-04 | Sanyo Electric Co., Ltd. | Dynamic image processing method and device and medium |
JP3695990B2 (en) * | 1999-05-25 | 2005-09-14 | 三菱電機株式会社 | Face image processing device |
JP2000347277A (en) * | 1999-06-03 | 2000-12-15 | Fuji Photo Film Co Ltd | Camera and method of pick up |
US6879705B1 (en) | 1999-07-14 | 2005-04-12 | Sarnoff Corporation | Method and apparatus for tracking multiple objects in a video sequence |
US6501857B1 (en) | 1999-07-20 | 2002-12-31 | Craig Gotsman | Method and system for detecting and classifying objects in an image |
JP2001067459A (en) * | 1999-08-26 | 2001-03-16 | Toshiba Corp | Method and device for face image processing |
US6526161B1 (en) | 1999-08-30 | 2003-02-25 | Koninklijke Philips Electronics N.V. | System and method for biometrics-based facial feature extraction |
JP4378804B2 (en) | 1999-09-10 | 2009-12-09 | ソニー株式会社 | Imaging device |
DE60045044D1 (en) * | 1999-09-14 | 2010-11-11 | Topcon Corp | Face photographing apparatus and method |
US6504951B1 (en) | 1999-11-29 | 2003-01-07 | Eastman Kodak Company | Method for detecting sky in images |
US6754389B1 (en) | 1999-12-01 | 2004-06-22 | Koninklijke Philips Electronics N.V. | Program classification using object tracking |
EP1107166A3 (en) | 1999-12-01 | 2008-08-06 | Matsushita Electric Industrial Co., Ltd. | Device and method for face image extraction, and recording medium having recorded program for the method |
US6516147B2 (en) | 1999-12-20 | 2003-02-04 | Polaroid Corporation | Scene recognition method and system using brightness and ranging mapping |
US6940545B1 (en) | 2000-02-28 | 2005-09-06 | Eastman Kodak Company | Face detecting camera and method |
US6807290B2 (en) | 2000-03-09 | 2004-10-19 | Microsoft Corporation | Rapid computer modeling of faces for animation |
US6301440B1 (en) | 2000-04-13 | 2001-10-09 | International Business Machines Corp. | System and method for automatically setting image acquisition controls |
JP3955170B2 (en) * | 2000-07-03 | 2007-08-08 | 富士フイルム株式会社 | Image search system |
US6965684B2 (en) | 2000-09-15 | 2005-11-15 | Canon Kabushiki Kaisha | Image processing methods and apparatus for detecting human eyes, human face, and other objects in an image |
US7038709B1 (en) | 2000-11-01 | 2006-05-02 | Gilbert Verghese | System and method for tracking a subject |
JP4590717B2 (en) | 2000-11-17 | 2010-12-01 | ソニー株式会社 | Face identification device and face identification method |
US7099510B2 (en) | 2000-11-29 | 2006-08-29 | Hewlett-Packard Development Company, L.P. | Method and system for object detection in digital images |
US6654507B2 (en) | 2000-12-14 | 2003-11-25 | Eastman Kodak Company | Automatically producing an image of a portion of a photographic image |
US6697504B2 (en) | 2000-12-15 | 2004-02-24 | Institute For Information Industry | Method of multi-level facial image recognition and system using the same |
GB2370438A (en) | 2000-12-22 | 2002-06-26 | Hewlett Packard Co | Automated image cropping using selected compositional rules. |
JP2002199202A (en) | 2000-12-26 | 2002-07-12 | Seiko Epson Corp | Image processing apparatus |
US6760465B2 (en) | 2001-03-30 | 2004-07-06 | Intel Corporation | Mechanism for tracking colored objects in a video sequence |
US6807250B2 (en) * | 2001-04-30 | 2004-10-19 | Eastman Kodak Company | Collimation device and method for acquiring a radiation image of a long body part using direct digital X-ray detectors |
JP2002334338A (en) | 2001-05-09 | 2002-11-22 | National Institute Of Advanced Industrial & Technology | Device and method for object tracking and recording medium |
US20020172419A1 (en) | 2001-05-15 | 2002-11-21 | Qian Lin | Image enhancement using face detection |
TW505892B (en) | 2001-05-25 | 2002-10-11 | Ind Tech Res Inst | System and method for promptly tracking multiple faces |
AUPR541801A0 (en) | 2001-06-01 | 2001-06-28 | Canon Kabushiki Kaisha | Face detection in colour images with complex background |
GB0116877D0 (en) | 2001-07-10 | 2001-09-05 | Hewlett Packard Co | Intelligent feature selection and pan zoom control |
US6516154B1 (en) | 2001-07-17 | 2003-02-04 | Eastman Kodak Company | Image revising camera and method |
WO2003009216A1 (en) | 2001-07-17 | 2003-01-30 | Yesvideo, Inc. | Automatic selection of a visual image based on quality |
US7027619B2 (en) | 2001-09-13 | 2006-04-11 | Honeywell International Inc. | Near-infrared method and system for use in face detection |
US7262798B2 (en) | 2001-09-17 | 2007-08-28 | Hewlett-Packard Development Company, L.P. | System and method for simulating fill flash in photography |
US7298412B2 (en) | 2001-09-18 | 2007-11-20 | Ricoh Company, Limited | Image pickup device, automatic focusing method, automatic exposure method, electronic flash control method and computer program |
KR100421221B1 (en) | 2001-11-05 | 2004-03-02 | 삼성전자주식회사 | Illumination invariant object tracking method and image editing system adopting the method |
US7162101B2 (en) | 2001-11-15 | 2007-01-09 | Canon Kabushiki Kaisha | Image processing apparatus and method |
US7130446B2 (en) | 2001-12-03 | 2006-10-31 | Microsoft Corporation | Automatic detection and tracking of multiple individuals using multiple cues |
US7050607B2 (en) | 2001-12-08 | 2006-05-23 | Microsoft Corp. | System and method for multi-view face detection |
US7035467B2 (en) | 2002-01-09 | 2006-04-25 | Eastman Kodak Company | Method and system for processing images for themed imaging services |
WO2003073359A2 (en) | 2002-02-26 | 2003-09-04 | Canesta, Inc. | Method and apparatus for recognizing objects |
US7254257B2 (en) | 2002-03-04 | 2007-08-07 | Samsung Electronics Co., Ltd. | Method and apparatus of recognizing face using component-based 2nd-order principal component analysis (PCA)/independent component analysis (ICA) |
US7174033B2 (en) | 2002-05-22 | 2007-02-06 | A4Vision | Methods and systems for detecting and recognizing an object based on 3D image data |
US20040001616A1 (en) * | 2002-06-27 | 2004-01-01 | Srinivas Gutta | Measurement of content ratings through vision and speech recognition |
US7227976B1 (en) | 2002-07-08 | 2007-06-05 | Videomining Corporation | Method and system for real-time facial image enhancement |
US7020337B2 (en) | 2002-07-22 | 2006-03-28 | Mitsubishi Electric Research Laboratories, Inc. | System and method for detecting objects in images |
US7110575B2 (en) | 2002-08-02 | 2006-09-19 | Eastman Kodak Company | Method for locating faces in digital color images |
US7474832B2 (en) * | 2002-11-21 | 2009-01-06 | International Business Machines Corporation | Personal video recording with storage space distributed among remote personal video recorders |
US7233684B2 (en) * | 2002-11-25 | 2007-06-19 | Eastman Kodak Company | Imaging method and system using affective information |
US7120279B2 (en) | 2003-01-30 | 2006-10-10 | Eastman Kodak Company | Method for face orientation determination in digital color images |
JP3984175B2 (en) | 2003-01-31 | 2007-10-03 | 富士フイルム株式会社 | Photo image sorting apparatus and program |
US7162076B2 (en) | 2003-02-11 | 2007-01-09 | New Jersey Institute Of Technology | Face detection method and apparatus |
US6846755B2 (en) * | 2003-02-18 | 2005-01-25 | Intel Corporation | Bonding a metal component to a low-k dielectric material |
JP2004294498A (en) * | 2003-03-25 | 2004-10-21 | Fuji Photo Film Co Ltd | Automatic photographing system |
JP4333223B2 (en) | 2003-06-11 | 2009-09-16 | 株式会社ニコン | Automatic photographing device |
US7792335B2 (en) | 2006-02-24 | 2010-09-07 | Fotonation Vision Limited | Method and apparatus for selective disqualification of digital images |
US7317815B2 (en) | 2003-06-26 | 2008-01-08 | Fotonation Vision Limited | Digital image processing composition using face detection information |
US7274822B2 (en) | 2003-06-30 | 2007-09-25 | Microsoft Corporation | Face annotation for photo management |
US7190829B2 (en) | 2003-06-30 | 2007-03-13 | Microsoft Corporation | Speedup of face detection in digital images |
US7689033B2 (en) | 2003-07-16 | 2010-03-30 | Microsoft Corporation | Robust multi-view face detection methods and apparatuses |
JP2005078376A (en) | 2003-08-29 | 2005-03-24 | Sony Corp | Object detection device, object detection method, and robot device |
US7424170B2 (en) | 2003-09-30 | 2008-09-09 | Fotonation Vision Limited | Automated statistical self-calibrating detection and removal of blemishes in digital images based on determining probabilities based on image analysis of single images |
US7274832B2 (en) | 2003-11-13 | 2007-09-25 | Eastman Kodak Company | In-plane rotation invariant object detection in digitized images |
AU2004311841B2 (en) | 2003-12-24 | 2008-10-09 | Walker Digital, Llc | Method and apparatus for automatically capturing and managing images |
US7551755B1 (en) | 2004-01-22 | 2009-06-23 | Fotonation Vision Limited | Classification and organization of consumer digital images using workflow, and face detection and recognition |
US7916173B2 (en) | 2004-06-22 | 2011-03-29 | Canon Kabushiki Kaisha | Method for detecting and selecting good quality image frames from video |
JP4928451B2 (en) | 2004-07-30 | 2012-05-09 | ユークリッド・ディスカバリーズ・エルエルシー | Apparatus and method for processing video data |
US7119838B2 (en) | 2004-08-19 | 2006-10-10 | Blue Marlin Llc | Method and imager for detecting the location of objects |
US7715597B2 (en) | 2004-12-29 | 2010-05-11 | Fotonation Ireland Limited | Method and component for image recognition |
US7454058B2 (en) | 2005-02-07 | 2008-11-18 | Mitsubishi Electric Research Lab, Inc. | Method of extracting and searching integral histograms of data samples |
US7620208B2 (en) | 2005-02-09 | 2009-11-17 | Siemens Corporate Research, Inc. | System and method for detecting features from images of vehicles |
US7715589B2 (en) * | 2005-03-07 | 2010-05-11 | Massachusetts Institute Of Technology | Occluding contour detection and storage for digital photography |
JP2006254229A (en) * | 2005-03-11 | 2006-09-21 | Fuji Photo Film Co Ltd | Imaging apparatus, imaging method and imaging program |
US7555149B2 (en) | 2005-10-25 | 2009-06-30 | Mitsubishi Electric Research Laboratories, Inc. | Method and system for segmenting videos using face detection |
US20070098303A1 (en) | 2005-10-31 | 2007-05-03 | Eastman Kodak Company | Determining a particular person from a collection |
US8488847B2 (en) | 2005-11-25 | 2013-07-16 | Nikon Corporation | Electronic camera and image processing device |
US7953253B2 (en) | 2005-12-31 | 2011-05-31 | Arcsoft, Inc. | Face detection on mobile devices |
US7643659B2 (en) | 2005-12-31 | 2010-01-05 | Arcsoft, Inc. | Facial feature detection on mobile devices |
US7804983B2 (en) | 2006-02-24 | 2010-09-28 | Fotonation Vision Limited | Digital image acquisition control and correction method and apparatus |
US7551754B2 (en) | 2006-02-24 | 2009-06-23 | Fotonation Vision Limited | Method and apparatus for selective rejection of digital images |
US7715598B2 (en) * | 2006-07-25 | 2010-05-11 | Arsoft, Inc. | Method for detecting facial expressions of a portrait photo by an image capturing electronic device |
-
2006
- 2006-07-26 US US11/460,218 patent/US7792335B2/en active Active
- 2006-08-03 WO PCT/US2006/030315 patent/WO2007097777A1/en active Application Filing
- 2006-08-03 EP EP06789329A patent/EP1989663A4/en not_active Withdrawn
- 2006-08-03 JP JP2008556300A patent/JP4970469B2/en active Active
-
2010
- 2010-08-03 US US12/849,597 patent/US7995795B2/en active Active
-
2011
- 2011-07-26 US US13/190,986 patent/US8285001B2/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20040170397A1 (en) * | 1999-06-03 | 2004-09-02 | Fuji Photo Film Co., Ltd. | Camera and method of photographing good image |
US20030160879A1 (en) * | 2002-02-28 | 2003-08-28 | Robins Mark Nelson | White eye portraiture system and method |
US20030190090A1 (en) * | 2002-04-09 | 2003-10-09 | Beeman Edward S. | System and method for digital-image enhancement |
US20040223629A1 (en) * | 2003-05-06 | 2004-11-11 | Viswis, Inc. | Facial surveillance system and method |
EP1748378A1 (en) * | 2005-07-26 | 2007-01-31 | Canon Kabushiki Kaisha | Image capturing apparatus and image capturing method |
Non-Patent Citations (2)
Title |
---|
HUANG W ET AL: "Eye tracking with statistical learning and sequential Monte Carlo sampling", INFORMATION, COMMUNICATIONS AND SIGNAL PROCESSING, 2003 AND FOURTH PAC IFIC RIM CONFERENCE ON MULTIMEDIA. PROCEEDINGS OF THE 2003 JOINT CONFE RENCE OF THE FOURTH INTERNATIONAL CONFERENCE ON SINGAPORE 15-18 DEC. 2003, PISCATAWAY, NJ, USA,IEEE, vol. 3, 15 December 2003 (2003-12-15), pages 1873 - 1878, XP010701737, ISBN: 978-0-7803-8185-8 * |
See also references of WO2007097777A1 * |
Also Published As
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US7792335B2 (en) | 2010-09-07 |
WO2007097777A1 (en) | 2007-08-30 |
EP1989663A1 (en) | 2008-11-12 |
US8285001B2 (en) | 2012-10-09 |
US20070201724A1 (en) | 2007-08-30 |
JP2009527983A (en) | 2009-07-30 |
JP4970469B2 (en) | 2012-07-04 |
US7995795B2 (en) | 2011-08-09 |
US20110280446A1 (en) | 2011-11-17 |
US20110033112A1 (en) | 2011-02-10 |
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